Empirical nexus between financial inclusion and carbon emissions: Evidence from heterogeneous financial economies and regions

We aim to investigate the empirical nexus between carbon emissions and financial inclusion for a panel of 74 countries from 2004 to 2020 based on the environment kuznets curve (EKC). Using the advanced panel data analysis framework of Driscoll–Kraay, Generalised linear model, and Prais-Winsten test for the entire sample and heterogeneous subsamples, we document an inverted U-shape relationship between carbon emissions and inclusive financial system. Notably, an inverted U-shape relationship is established in developed, emerging and frontier economies except in standalone economies. Furthermore, the analysis of region-wise subsamples reveals that nonlinear relationship varies across regions. The heterogeneous response of financial inclusion in curtailing environmental degradation provides vital policy insights. It suggests that financial inclusion can be used as a mitigation measure based on well-structured and robust regulatory and legal frameworks. These frameworks would create synergy effects of financial inclusion in designing policies and addressing issues related to sustainable development and climate change.


Introduction
The augmented awareness of climate change and environmental sustainability calls for low-carbon economies. The significance of reduced carbon emissions (CO2) has been more pronounced after recent initiatives such as 26th United Nations Climate Change Conference (COP26), 1 Paris Climate Change Act, 2 Energy Bill, 3 among others. The United Nations' sustainable development goals (SDGs) 4 urge countries to take serious actions to combat climate change and its impacts by reducing carbon emissions. During the COP26, participants agreed that money is a vital tool to achieve the said goals. However, the transition to carbon neutrality and environmental sustainability is impossible without improving financial services, resources and markets [1]. Nevertheless, financial and economic development should be well aligned with SDGs as otherwise, it may add to carbon emissions and environmental degradation [2,3].
In the economic development process, the role of financial inclusion has received massive attention and interest from policymakers and researchers [4]. Besides the role of financial inclusion in technological progress and sustainable economic growth, contemporary researchers argue that an inclusive financial system has equally affected the quality of the environment, particularly carbon emissions [5]. Theoretically, an inconclusive relationship exists between an inclusive financial system and environmental sustainability [6][7][8].
One strand of researchers argued that financial inclusion enhances environmental sustainability and reduces CO2 emissions through increased spending on research & development and technological innovations [9,10]. More specifically, governments and firms tend to adopt environmentally friendly technologies that reduce carbon emissions and enhance environmental sustainability due to the low cost of borrowing [11]. On the contrary, other strands of literature argue that an accessible financial system with affordable financing boosts industrial and manufacturing activities, increasing CO2 emissions and damaging environmental quality [12,13].
Besides this, the extant literature also supports the nonlinear relationship between carbon emissions and financial sector development [8,14]. Ref. [10] find an asymmetric impact of financial inclusion on CO2 that varies geographically. Moreover, environmental degradation is vast if the country is in an early development phase. In contrast, economic growth enhances ecological preservation in the later development phase. Empirically, Refs. [15,16] find an inverted U-shaped relationship between an inclusive financial system and CO2 emission. Likewise, Ref. [8] observe a nonlinear relationship between carbon emission and financial sector development. However, they argued that the nonlinearity between environmental quality and an inclusive financial system is linked to a robust governance mechanism. Therefore, strict adherence to environmental regulations based on environment, social, and governance (ESG) is the key to ensuring sustainable development. In other words, this relationship may not be nonlinear in those countries or regions with weak ESG-related governance mechanisms. Hence, the nonlinear nexus between environmental sustainability and financial inclusion may vary across different levels of economic development and governance mechanisms.
These inconsistencies in the empirical literature create an opportunity to revisit the empirical nexus between an inclusive financial system and CO2 emissions. The objective of our study is to investigate the link between CO2 and financial inclusion, preserving the heterogeneity of financial development of sample economies and regions.
Our study offers various contributions to the literature. First, contemporary empirical studies by Refs. [8,17] have failed to consider different phases of the financial development of countries while investigating the empirical nexus between the inclusive financial system and CO2 emissions. As technological progress, economic growth and capital accumulation could vary across countries. Countries with well-established financial systems may have less information asymmetry and low-cost funds available to households and businesses compared to poorly developed financial systems [18]. However, it remains unclear from the prior literature whether different phases of financial development matter when investigating the nonlinear nexus between an inclusive financial system and CO2 emissions. Keeping this in view, the current study investigates the empirical nexus between CO2 emissions and inclusive financial system in heterogeneous financial economies such as developed, developing, frontier, and standalone economies. Second, our study aids in fully comprehending the carbon emissionsfinancial inclusion nexus to fight climate change and to make a close estimate of CO2 emissions across various regions. It is accomplished by testing financial inclusion-based EKC in multiple areas. If diverse EKC situations are discovered for different emission types, a one-size-fits-all strategy cannot be the best course of action. As discussed above, it is crucial to closely evaluate the impact of inclusive financial systems on carbon emissions across various regions to give policymakers more significant insights.
We test the Environmental Kuznets Curve (EKC) hypothesis to identify the association between CO2 emissions and inclusive financial development across different regions. These regions, Africa, America, Asia, Europe and the Middle East, are of great importance to be investigated for various reasons. First, these regions broadly vary along levels of financial, economic and governance [19][20][21]. Second, these regions have experienced rapid economic development and globalisation over the last few years. However, such a pronounced economic development is subject to environmental consequences [1,22,23]. For instance, the Asia region recently produced 17.74 billion metric tons of carbon emissions in 2021, which is higher than the total emissions in all regions in 2021.
Furthermore, North America is the next most polluting region in the same year, with 5.6 billion metric tons of carbon emissions. Overall, carbon emissions in most of these regions increased by 5% in 2021 as compared to 2020 levels (Tiseo, 2022). 5 Third, the scant empirical literature provides insufficient support to the EKC hypothesis testing region-wise comparisons of financial inclusioncarbon emissions nexus.

Theoretical perspective of financial inclusion and environmental degradation
Financial development cannot be separated from financial inclusion. Therefore, discussing financial development's empirical and theoretical underpinnings is vital to building a connection between an inclusive financial system and CO2 emissions [1,24]. Theoretically, researchers have differing opinions about how related inclusive financial development and environmental sustainability are (Jiang & Ma, 2019; [25,26]. One constituent of the literature suggests that financial development lowers CO2 emissions by mitigating financial constraints with low borrowing costs for upgrading equipment and production technologies [27]. Likewise, Ref. [28] suggest that financial growth promotes the reduction of carbon emissions.
On the other hand, the extant literature contends that increased carbon emissions caused by financial development worsen environmental degradation. Because a well-functioning financial system provides low-cost financing for expanding production capacity, which leads to deterioration of environmental quality [29]. The third strand of literature supports nonlinearity between CO2 emissions and inclusive financial progress [14]. Theoretically, Ref. [29] introduced the concept of EKC. They argued that environmental quality is linked with the economic development phases: a low development stage is associated with environmental degradation, whereas the advantages of strong economic development preserve the environment quality.

Empirical literature and hypothesis development
The literature has paid huge attention to the empirical nexus between CO2 emissions and inclusive financial system in recent years [4]. However, the results are conflicting; few studies have found a negative relationship between an inclusive financial system and CO2 emissions, while others have documented a positive association between them. Studies that support that financial progress lowers Nonlinear relationship was found between FI and carbon emissions environmental quality include [1,4,[30][31][32]33] among others. The existing literature recognises the constructive role of financial development in struggling with inclusive economic growth, climate change and sustainable development [34]. For instance, Ref. [31] investigated data from 39 SSA countries between 2004 and 2014 and found that economic growth in SSA countries lowers carbon emissions. According to Ref. [1], who used a static panel data framework, there is an unfavourable link between CO2 emissions and financial development in China. The reduction of carbon emissions and other pollutants is positively correlated with an inclusive financial system, according to Shahbaz et al. (2022) [10], who studied 30 Chinese provinces from 2011 to 2017. The same idea is supported for China by Ref. [33] using an ARDL approach. Ref. [32] also classified 33 OECD economies into two groups based on their degree of globalisation: highly globalised and lower globalised. The study found that the impact of inclusive financial progress on CO2 emission was negative for each group. While analysing a panel dataset of 19 developing countries from 1990 to 2013, Ref. [35] confirmed the negative influence of financial progress on CO2 and argued that financial progress contributes to environmental sustainability. Ref. [1] consider an advanced panel data framework for 23 economies from 1985 to 2011 and support that financial growth reduces CO2 emissions.
On the contrary, many studies claim that financial inclusion deteriorates environmental quality [7,25,[36][37][38][39]. Using Driscoll-Kraay standard errors panel data models for 31 Asian countries from 2004 to 2014, Ref. [7] find that inclusive financial growth led to higher CO2 emissions in the sample region. Similarly, through second-generation panel data techniques, Ref. [37] documented that financial inclusion increased CO2 emissions. Additionally, Ref. [40] looked into the long-term and short-term relationships between inclusive financial and CO2 emissions from 1971 to 2010 using the Panel ARDL technique. Their research shows that financial inclusion causes the environment to degrade much more. Ref. [41] found that inclusive financial significantly and positively influence CO2 emissions in South Asia.
The literature also supports the nonlinear relationship between financial growth and environmental sustainability. For instance, Ref. [42] determine the nonlinearity between CO2 emissions and inclusive financial for Central Asian and European economies from 2010 to 2019 and confirm the inverted U-Shaped EKC. While taking 25 OECD economies from 1971 to 2007, Ref. [43] found a nonlinear relationship between CO2 emissions and financial growth. Ref. [8] used the EKC framework and suggested an inverted U-shaped relationship was found between CO2 emissions and financial development. Similarly, Ref. [44] confirms the inverted U-shaped relationship between CO2 emissions and financial growth of 52 countries from 2001 to 2014. Using the Panel Dynamic Common Correlated Effects (CCE) approach, Ref. [17] examined the OIC countries from 2004 to 2018. Their findings support the nonlinear relationship between inclusive financial development and CO2 emissions for all OIC countries, including all panels. The literature review is summarised in Table 1. Based on the literature above, we hypothesise as follows:

H1. There exists an inverted U-shaped EKC relationship between financial CO2 emissions and financial inclusion.
Notably, the extant literature advances the literary work and offers valuable insights, but the empirical nexus between inclusive financial and CO2 emissions are inconclusive and inconsistent. The two gaps primarily support further deliberation and exploration of this nexus. First, although there is a sufficient amount of research on the FI-CO2 emissions nexus, the existing literature is still at its infancy stage when it comes to the said nexus regarding the level of financial development of countries. Our study examines the EKC hypothesis between financial inclusion and carbon emissions in heterogeneous financial economies such as developed, frontier, developing and standalone capital markets. While analysing the effects of inclusive financial on CO2 emissions, Ref. [8] neglected to consider the different phases of financial inclusion in sample countries. Hence, the study argues that financial inclusion for facilitating economic growth, capital accumulation, and technological progress differs through governments with different phases of financial development. Second, the study tests the EKC hypothesis between the inclusive financial system and CO2 emissions across different regions such as America, Asia, Europe, the Middle East and Africa through advanced statistical techniques such as Driscoll-Kraay standard errors (D-K), GLM (Generalised Linear Model), and Prais-Winsten to produce consistent and efficient parameters as a robustness check since these regions vary along economic development, political, and level of governance. Our study is unique in providing fresh evidence about the heterogeneous and nonlinear relationship between carbon emissions and financial inclusion.

Research design
The data related to financial inclusion, carbon emissions, and macroeconomic indicators were collected from Global Findex Database and World Development Indicators (WDI). For this purpose, a sample of 74 heterogeneous financial economies consisting of developed markets (22), developing markets (22), Frontier Markets (19), and Standalone Markets (11) is based on MSCI classification. For further analysis, these sampled countries were also divided into different region such as Europe, the Middle East and Africa regions (50), Asia (13) and America (11). The sample details are provided in Appendix Table A1.

Operationalisation of variables
For empirical analysis, the study categorises the variables into a dependent variable (carbon emissions), an independent variable (financial inclusion). The study also employed a few control variables, which include the gross domestic product (GDP), trade openness (TO), population growth (POG), industrialisation (IND), and human capital (HC).
In literature, the concept of financial inclusion has recently emerged. We constructed financial inclusion index based on five different proxies. These proxies are (i) bank deposit amount (ii) bank credits, (iii) number of commercial bank branches available for 100,000 adults, (iv) number of ATMs available for 100,000 adults, and (v) Institutions of commercial banks [7,45]. The first two represent usage, and the latter three indicate financial services' availability [46]. By following [47], all these proxies were normalised using the following normalisation techniques via equations [1][2][3][4]: a) Z-score normalisation: The z-score normalisation will be measured as follows.
where, X is a group average and δ is a standard deviation.
b) min-max normalisation: The minimum and maximum observations are used to measure normalised scores, as under.
where, X min and X max are the minimum and maximum values in the data set respectively. c) Softmax normalisation: Using exponential functions, mean and standard deviation, it calculates normalised scores, as follows.
where, e is the exponent, X is a group average and δ is a standard deviation. Principal component analysis (PCA) was used to construct an index for financial inclusion. As, prior literature most widely used PCA due to several reasons. First, to lessen the dimensionality of data and build composite indicators index, PCA removes excess information and extracts hidden relationships and features [48]. Second, we used two tests before the PCA, namely Bartlett's and Kaiser-Meyer-Olkin (KMO) to confirm the validity of the chosen proxies to develop an index for financial inclusion. The value of Bartlett's test was significant (P < 0.05) and the value of KMO (>0.5) indicates the suitability of PCA. The results are reported in Table 2.
PCA is performed in two steps. (i) various components were estimated to identify the lowest pairwise correlation and the variations in the original variable. (ii) only those components were retained whose eigen values was greater than 1 to build the Financial inclusion index (Gujarati & Porter, 2009). Tables 3 and 4 report the cumulative variations of each component and pattern matrix of PCA for whole sample as well as subsamples.

Econometric model
For theoretical foundation, the influence of inclusive financial system on CO2 emissions is investigated using the stochastic effects by regression on population, affluence, and technology (STIRPAT) [49]. The STIRPAT model is: (4) where I it, P it, A it , and T it are environmental effects, population, affluence and technology for country i at time t, respectively. For financial inclusion, we extend the STIRPAT model. Several control variables, namely gross domestic product (GDP), trade openness (TO), population growth (POG), industrialisation (IND), and human capital (HC) are added based on the previous literature [8,50] Z. Khan et al.,202. The baseline model is: where Co2 it is the logarithm of CO2 emissions, FI it is the financial inclusion index, FI 2 is the squared term of Financial inclusion (An inverted U-shaped EKC curve when δ 1 > 0, δ 2 <0). GDP is the gross domestic product and GDP 2 stands for the squared term of GDP. Further, Control represents the control variables such as trade openness, industrialisation, population growth, and human capital.

Estimation techniques
The panel data was analysed using the following steps to empirically examine the impact of inclusive financial on CO2 emissions across different regions: (i) Cross-sectional dependency was checked using the cross-sectional dependence test proposed by Ref. [51].
(ii) For Eq. (5), we employed Driscoll-Kraay (D-K) standard errors in the full sample. Driscoll-Kraay is appropriate in case of cross-sectional dependency and short time period [45]. Moreover, Driscoll-Kraay deals with the problem of heteroscedasticity, serial correlation and contemporaneous correlation both in balanced and unbalanced panels [52]. (iii) Using Driscoll-Kraay procedure, the empirical nexus between inclusive financial and CO2 emissions was also analysed in subsamples of heterogeneous financial economies and across different regions. (iv) For robustness check, the study also employed GLM (Generalised linear model), and Prais-Winsten    test in the entire sample and subsamples.

Summary statistics
The findings of summary statistics for each variable are shown in Table 5. The carbon emission averages and standard deviations (M = 7.374, SD = 6.341) are somewhat lower than the whole sample values given by Ref. [8]. The summary statistics show that the average number of ATMs and branches of commercial banks per 100,000 adults are higher than those reported in Ref. [8]. Similarly, the outstanding deposits and loans (per cent GDP) is also higher than reported by Ref. [7] for the Asia region. This shows that certain countries have better financial inclusiveness than others. The mean and standard deviation of trade openness are among the control variables (M = 90.435, SD = 55.717). Furthermore, Fig. 1 shows that the relationship between carbon emission and financial inclusion is nonlinear and makes an inverted U-shaped relationship over the sample period. Moreover, carbon emissions kept increasing even when financial inclusion decreased from 2009 to 2013 with small dips. Although since 2008, both financial inclusion and carbon emissions started growing, the rate of increase for carbon emissions was relatively high compared to that of financial inclusion. Both carbon emissions and financial inclusion declined abruptly in 2020, on the onset of Covid-19. 6 The nonlinear trend of financial inclusion and carbon emissions in subsamples such as developed, emerging, and frontier markets. However, Fig. 5 reveals the linear trend of financial inclusion and CO2 emissions in standalone countries.

Cross-sectional dependence tests
The results of cross-sectional dependency test using [51] are reported in Table 6. Ref. [7] documented that CD test are best suited to shorter time series but larger cross-sectional data. The results of CD tests for the full sample and subsamples reveal that all the variables are statistically significant at 1% level, rejecting the null hypothesis of cross-sectional independence. Hence, cross-sectional dependency exists amongst the variable across full sample and subsamples.

Financial inclusion and carbon emissions (full and subsamples)
We analysed the baseline Eq. (5) through advanced statistical techniques in the full sample and subsamples to achieve consistent and efficient estimates even in serial correlation, heteroscedasticity and cross-sectional dependency. Table 7 reports the results of the nonlinear effect of financial inclusion on carbon emissions for the full sample. The financial inclusion coefficient is significant and positive. In contrast, the coefficient of a square of financial inclusion was found to be negative (δ1 > 0, δ2<0), indicating an inverted Ushaped relationship between CO2 and inclusive financial. Our results support the EKC hypothesis for the whole sample in the long run. Additionally, our findings are consistent with the theory that, in the early stages, a sound financial system provides a mechanism for mitigating risk and effective resource pooling that promotes industrial activities for better economic prospects though worsening environmental quality. Later on, after a turning point, economic development ensures environmental preservation [8,42]. Tables 8-11 reports the results of the nexus between inclusive financial development and CO2 emissions for developed, emerging, frontier and standalone capital markets. The coefficients of financial inclusion and squared term of financial inclusion reveal that the EKC hypothesis exists in developed, emerging and frontier economies. However, the EKC hypothesis does not hold in standalone economies. Our findings align with the theoretical assumptions that different countries may affect financial development regarding green economic growth, technical advancement, and capital accumulation. For instance, compared to the countries with less developed financial systems, those with well-established financial systems have high technological progress, economic expansion, reduced information asymmetry, and lower costs for people and businesses to obtain credit [4]. As a result, it is unlikely to expect that nations at different stages of financial development would see the same effect on carbon emissions from inclusive financial progress [43]. The graphical representation of the nexus between financial inclusion and carbon emissions in Figs. 2-5 also confirms that an inverted U-shaped relationship exists in developed, emerging, frontier and standalone capital markets except for standalone economies. Likewise, Fig. 6 also confirms that linear nexus of financial inclusion and CO2 emission in standalone economies.
In a nutshell, the inclusive financial system and its square terms have a significant positive and negative impact, respectively on the intensity of carbon emission. Similarly, several studies, such as [42,53] supported the notion that the non-monotonic impact of financial inclusion is not always linear on CO2 emissions. As a result, the link between inclusive financial systems and carbon emission intensity is inverted U-shaped in developed, emerging and frontier economies. Consequently, the argument that financial development might not have a monotonic impact on carbon emission intensity is further supported by the fact that inclusive financial growth increases carbon emission intensity. However, carbon emissions intensity decreases after a certain threshold level of financial development. The nonlinear nexus between inclusive financial development and environmental quality is weak in standalone countries. Overall, empirical results validate the existence of an inverted-U relationship between CO2 emissions and financial inclusion, indicating financial inclusion as a significant and positive driver in exerting environmental sustainability, consistent with [54] (2022) and [24].
Moreover, the nonlinear nexus between financial inclusion and carbon emission were also examined across different regions. The results in Tables 12-14 reveal that financial inclusion-based EKC exists for Europe, the Middle East, Africa and Asia, whereas it does not hold for America. The presence of EKC in our results suggests a nonlinear relationship between CO2 emissions and inclusive financial development. The inconsistent behaviour of financial inclusion based on EKC is in line with the theoretical assumptions that ESGrelated regulations and incentives for businesses and individuals to promote green growth varies across regions [20]. Hence, a policy that fits everyone is not an excellent way to ensure sustainable development [17].
Furthermore, by following the reasoning of [8], we also test the significance of inclusive financial system-based EKC in the presence of regular EKC across whole and subsamples, thereby incorporating the square term of GDP in Eq. (5). Our findings across whole and subsamples suggest the presence of EKC, and these results are robust and statistically significant for both the coefficients and squared terms of financial inclusion. It further shows that the financial inclusion-based EKC is independent of the regular EKC.
Regarding the region-based analysis, the long-term impact of financial inclusion on carbon emissions in Africa, Asia, Europe, and the Middle East is negative and promotes environmental sustainability. These regions have focused on alternate energy sources, including renewable energy, which allows for the necessary level of financial development that reduces carbon emissions. Several studies confirm the existence of the EKC inverted U-shaped hypothesis and the nonlinear negative impact of squared financial     [42], South Africa [55], Chine [56], UAE [57], on the other hand, demonstrates that none of the financial development indicators had a significant nonlinear influence on CO2 emissions in 46 sub-Saharan African countries. A linear relationship was observed between financial inclusion and carbon emissions in OECD and Asian countries [7,26]. According to these studies, financial development makes it easier to acquire loans for starting firms with high energy use, which adds to environmental degradation. In addition, financial growth also lowers transaction costs and makes lending to the private sector substantially more affordable. As a result, new projects are initiated without considering their environmental effects, which pollutes the environment.

Robustness check
Robustness tests are applied to verify the reliability of our inverted U-shaped relationship between carbon emission and financial inclusion. We employed GLM and Praise-Winsten panel data framework for full and subsamples. The GLM and Praise-Winsten test are consistent with our established results that inverted U-shaped relationships exist in developed, emerging and frontier markets except in standalone economies. Concerning the testing of region-wise nonlinearity nexus between the inclusive financial system and CO2 emissions, the results further validate our previous findings that the impact of financial inclusion-based EKC varies across regions.
Overall, the findings support the notion that the inverted U-shaped EKC hypothesis holds in the long run. The results support the notion that an inclusive financial system contributes to environmental degradation beyond inevitable financial development. Moreover, the non-persistent behaviour of financial inclusion-based EKC across the level of financial development and regions is consistent with the notion that the nonlinearity between financial sector development and carbon is conditioned upon solid governance mechanisms and strict environmental regulations [8]. The findings of this study shared common grounds with empirical studies such as [8,17], who have supported the nonlinear impact of financial inclusion on CO2 emissions.

Conclusion and policy implications
The current study investigated the empirical nexus between the financial inclusion and carbon emissions of full and heterogeneous subsample countries based on the EKC hypothesis. We analyse this relationship across different regions in view of STIRPAT framework. Our results from the D-K test illustrate that the inverted U-shaped relationship exists between CO2 and inclusive financial system in the entire sample and across heterogeneous subsamples. For the robustness check, we used GLM and Praise-Winsten panel data framework. Our results are consistent with our established results that inverted U-shaped relationships exist in developed, emerging and frontier markets except for standalone economies. Furthermore, the region-wise analysis also suggests the non-persistent behaviour of Table 9 The Nonlinear relationship between Financial Inclusion and Carbon Emissions (Emerging Markets).       financial inclusion-based EKC across regions. We find inverted U-shaped relationships in Europe, the Middle East, Africa, and Asia. Further, we also document that this relationship does not exist in America. We have derived several critical policy implications from the results. First, to attract private investment for low-carbon projects, financial inclusion can be used as a prerequisite. As financial services leverage private investment, that first needs the establishment of financial infrastructure. Ref. [58] documented that financial institutions are essential for innovative ideas such as the spillover effect of taxes and green credit guarantee schemes (GCGSs) that reduces the risk and attract private investors. The government should widen the financial coverage provided by the credit market, which led to the emergence of financial infrastructure by attracting financial institutions to meet the increased demand for financial services. Second, due to the heterogeneous response of financial inclusion in curtailing environmental degradation, governments should set a regulatory framework that promotes a reliable and inclusive financial system. In addition, consumers should be encouraged to enhance their financial literacy to best use the available financial services. Third, policy makers and regulators should identify issues related to financial regulation, inclusion and development as it is pertinent to implement policies that could reduce carbon emissions. Thus, a comprehensive green financing program should be developed by each country to achieve the 2030 SDGs of carbon neutrality and environmental sustainability. Additionally, authorities in these economies should adopt mitigating methods such as adopting and implementing digital financial inclusion in the future.
Besides, the study has a few limitations. First, this study covered 74 countries, regions, and subsamples to examine the nexus between financial inclusion and carbon emissions. Therefore, future studies could consider analysis based on a single country because these countries' economic, political, ethnic, cultural, and religious attributes vary. Second, the focus of this study remains solely on the relationship between financial inclusion and carbon emissions. However, other variables, such as the level of technological innovation and governance system of sample countries, may also affect environmental sustainability. Therefore, future studies may examine the moderating role of governance and technological innovation on the relationship between financial inclusion and environmental degradation. Third, to broaden policymakers' understanding, future researchers could use a more extensive set of financial inclusion    proxies based on penetration, availability, and usage of the financial system to construct the financial inclusion index and check the relationship with carbon emissions using the same analytical framework.

Author contribution statement
Shahzad Hussain: Conceived and designed the experiments. Razia Gull: Performed the experiments. Sabeeh Ullah: Contributed reagents, materials, analysis tools or data. Abdul Waheed: Analysed and interpreted the data. Muhammad Naeem: Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement
The data is Publicly available on world bank website.

Declaration of interest's statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.